HPC Series: Calculating with random numbers: An introduction to Monte Carlo methods (5/6)

by Christian Schmidt-Sonntag

Monday 2 Jun 2025, 12:00 → 13:30 Europe/Zurich

online via Zoom

Monte Carlo methods are a powerful class of algorithms used to solve problems through random sampling—and they’re behind a significant share of HPC workloads across research domains.

In this 90-minute hands-on session, participants will explore the basics of Monte Carlo integration and learn how stochastic approaches can be applied to complex problems. Using a Python notebook, you'll write a simple pseudo-random number generator and experiment with code snippets and simulations to build your understanding.

🔹 No prior experience with Monte Carlo required
🔹 Ideal for scientists and researchers using Python
🔹 Includes live coding, code snippets, and simulations

About the instructor: Christian Schmidt is a theoretical physicist at Bielefeld University, working in the field of lattice Quantum Chromodynamics. He has a strong background in high performance computing and numerical methods and is supporting users of the GPU Cluster at Bielefeld University.